GitLab

* Fix gradient accumulation

- Add ``is_scaled_loss`` flag to support both scaled / unscaled loss
- Add a method `scale_grad_by_num_grads_to_accum`to handle gradient accumulation using unscaled loss more explicitly
- Fix ``test_grad_accum`` and``test_set_num_gradients_to_accumulate``
- Add tests for gradient

Co-authored-by: Min Xu <min.xu.public@gmail.com>

* Fix CI

* ci pythonpath

This is no longer needed since isort's version is 5.10

Also fix black version to 22.3.0 to fix issue with click
dependency.

Update files that now fail with new version of black {a = 2 ** 4} ->
{a = 2**4}

* update pytest versions

* [test] test related changes

- upgrade to newer pytorch versions
- added function to make test more deterministic on A100 and TF32
- fixed some tests so that they are correctly skipped on a single GPU system

* more fixes

* formatting overly long lines

* format

* better test without trigger a warning

* fix an optim state bug with newer pytorch

- adam optimizer seems to return "step" as a singleton tensor now in the
nightly build
- this fixes it assumeing non-tensor value can still be loaded back by
the optimizer

* improve oss.py

- use min_loss for regression checking is a bit more reliable
- also increased the num epochs from 10 to 12

* small oss.py fix

* Update fairscale/nn/data_parallel/fully_sharded_data_parallel.py
Co-authored-by: Min Xu <min.xu.public@gmail.com>

* adding an assert + corresponding unit test
* updated changelog
* adjusting the adascale tests

* [test]: test with py39 + torch 1.8 nightly

* version fix

* more fix

* fix version function for nightly version

* fix torch_pg build

* invalidate cache

* separate benchmark requirements

* comment

* fixed mypy

* fixed a test

* [test]: test adascale with oss

* minor fix

* add a small comment

* refactor: moved find_tensor_by_shape

* refactor: move test golden data into its own module

* refactor: simplied the train function

* refactor: added comments as suggested

* adding the pytest timeout plugin to properly root out hanging tests
* removing redundant code, slightly more reasonable timeout, works on single cuda
* finding the root bug for some of the cpu hangs, rpc init
* propagating all the rpc init test changes to the pipe and model parallel tests

* [feat] sync adascale from internal repo

- tbd

testing: tbd

* Update argument document of __init__

* update documentation around set_num_gradients_to_accumulate

* added checking code for proper API calling places

* rename internal APIs to make them internal

* updated changelog

* added support for add_param_group and its unit test

* added unit test for set_num_gradients_to_accumulate

* added debias_ewma unit test

* fixed test_set_num_gradients_to_accumulate (need zero_grad() call)

* added missing zero_grad() to test_lr_scheduler

* fixed test_add_param_group with respect to optim.zero_grad()

* added test_gradient_value

* added test_scale_not_equal_default for scale != world_size * grad_accum

* added test_unhook()

* removed print statements

* fixed a typo

* addressed Ben's comment

* [doc]: AdaScale example and notes

* formatted notes correctly as suggested by Benjamin

* added feature and unit test to make sure lr_scheduler works

* update the example with lr_scheduler

* fixed doc with "make html"

* addressed Mike's suggestions

* better ddp adascale tests

* make sure the single node test use the same test cases and expected gains

* added unit test that covers smoothing factor

- tested by re-introducing the bug and see the test fail as expected.

* added AdaScale to README

* [adascale] added gradient accumulation

- added gradient accumulation
- tested with cifar full trainings with different value of accumulation
and verified the full accuracy is obtained
- also removed the patch optimize flag until we need it

* [adascale] adding pytest

- added basic and ddp tests and grad_accum
- closes #195

* added changelog

* added ddp grad_accum test

* moved ddp and non-ddp tests into separate files

* added checkpoint test

* more doc

* addressed Mike's comments